Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
Tavily Dynamic Search
Keep large raw web payloads on disk and return only the evidence needed for the task. This is useful when using --include-raw-content, combining several queries, or extracting multiple long pages. Do not use this workflow for a simple lookup that a normal tvly search --json can answer directly.
Before running
Search and extract support capped keyless access. Run them directly when tvly is available. If tvly is missing, follow the tavily-cli setup. Do not look for an API key or authenticate before the first request. If the keyless cap is reached in an interactive session, run tvly login to open browser OAuth, then retry the blocked request once. In an unattended environment, report the cap and authentication options instead of starting an interactive flow.
Workflow
- Search broadly without raw content and inspect titles, URLs, scores, and
snippets.
- Fetch full content only for the best sources.
- When raw output could be large, save it with
-oand filter the file before
printing anything to the model context.
- Preserve source URLs beside every extracted fact.
When the user restricts evidence to official or named domains, validate the hostname of every selected URL during local filtering. --include-domains narrows the search but is not proof that every returned result belongs to an allowed host. If full-page extraction is unavailable, label conclusions as search-snippet evidence instead of implying that the page body was verified.
Keep the process in one turn when the relevant sources and filters are already known. Use another turn only when the first search changes what should be extracted.
Create a unique temporary task directory before saving evidence so concurrent agents do not overwrite one another. Python's tempfile.mkdtemp() is available when mktemp is not permitted. Reuse that directory for all raw and filtered artifacts from the task.
Small result: filter a direct JSON response
For a small search response, a pipe is enough:
tvly search "query" --max-results 5 --json | python3 -c '
import json, sys
data = json.load(sys.stdin)
for result in data.get("results", []):
score = result.get("score") or 0
title = result.get("title") or ""
print(f"[{score:.2f}] {title}")
print(result.get("url", ""))
print(result.get("content", "")[:300])
'Do not discard stderr. Authentication failures, keyless-cap messages, and API errors are actionable and must remain visible.
Large result: save first, then filter
Use the CLI's file output so raw page content does not pass through the tool response:
tvly search "query" \
--include-raw-content markdown \
--max-results 8 \
--json \
-o /tmp/tavily-search-results.jsonThen print only bounded evidence:
python3 -c '
import json
from pathlib import Path
data = json.loads(Path("/tmp/tavily-search-results.json").read_text())
for result in data.get("results", []):
title = result.get("title") or ""
url = result.get("url") or ""
print(f"## {title}")
print(f"URL: {url}")
print((result.get("raw_content") or result.get("content") or "")[:1200])
print()
'Adjust the filtering logic to the question. Prefer relevant paragraphs or fields over fixed character slices when the target information is known. Aim for roughly 150-600 tokens per source unless a table or code block genuinely requires more.
Targeted extraction
When search identifies the right URLs, extract only those pages:
tvly extract "https://example.com/article" \
--json \
-o /tmp/tavily-extract-results.jsonFor topic-focused pages, let Tavily reduce the response before local filtering:
tvly extract "https://example.com/docs" \
--query "authentication API" \
--chunks-per-source 3 \
--json \
-o /tmp/tavily-extract-results.jsonMultiple queries
For multi-angle research, run a small set of focused searches, deduplicate by URL, and rank before extracting. Use subprocess.run(..., capture_output=True, text=True) when orchestrating commands in Python. Check returncode; if a command fails, surface its stderr and stop or retry deliberately. Never use a blanket except Exception: continue that hides missing evidence.
Response shapes
tvly search --json returns query, optional answer, results, and response_time. Each result commonly contains url, title, content, score, and optional raw_content.
tvly extract --json returns results, failed_results, and response_time. Each successful result commonly contains url, raw_content, and optional images.
Treat fields as optional and use .get() while filtering. Inspect failed_results instead of assuming every requested URL succeeded.
Useful options
| Option | Purpose |
|---|---|
--max-results | Bound the search result count; default 5, maximum 20 |
--depth | Choose ultra-fast, fast, basic, or advanced |
--time-range | Restrict results to day, week, month, or year |
--include-domains | Restrict results to a comma-separated list of trusted domains |
--exclude-domains | Exclude a comma-separated list of domains |
--include-raw-content | Include full content as markdown or text |
-o, --output | Save the complete response to a file |
Use jq only for short filters when Python is unavailable:
tvly search "query" --json | jq '[.results[] | {title, url, score, content}]'
